Device and method for estimating battery health

Abstract

The present invention discloses a method for estimating a battery health, comprising: collecting measurements of a battery during multiple charge and discharge cycles; assigning a score to the measurements according to a scoring rule stored in a memory of a device; and calculating the battery health based on an average of the measurements, each measurement having an assigned score greater than a threshold. In this manner, as the battery ages, the battery health meter can adjust the estimated battery health by changing the way the battery measurements are collected and scored. Adjustments can be made continuously during the life of the battery. Therefore, as more battery measurements are collected and analyzed, the estimate of the battery health can be continuously improved to obtain a more accurate estimate of the battery health and information related to the battery health in real time.

Description

Technical Field

[0001] The present invention relates to the field of electrical technology, and in particular to a device and method for estimating battery health status. Background Art

[0002] Rechargeable batteries are commonly used in modern electronic devices. To prevent unexpected device shutdowns and optimize device power and performance, devices often include battery monitoring systems to monitor battery status, such as state of charge (SOC) and state of health (SOH). SOC is the ratio of a battery's remaining capacity (measured in milliampere-hours (mAh)) to its maximum available capacity (Cmax). When the SOC is 100%, the battery is fully charged; when the SOC is 0%, it is fully discharged. However, Cmax decreases as the battery ages. For example, a 100% SOC for an aged battery might be equivalent to 75%–80% SOC for a new battery.

[0003] SOH is the ratio of Cmax to the battery's rated capacity. Rated capacity is typically provided by the battery manufacturer and represents the maximum capacity of a new battery. This means that Cmax equals the rated capacity when the battery is new. A battery's SOH indicates its ability to store and release electrical energy compared to when it was new. A new battery's SOH is 100%, and as the battery ages, the SOH decreases. When the SOH falls below a threshold, the battery may need to be replaced.

[0004] Accurate SOC and SOH estimation can prevent unexpected downtime and improve system performance and reliability. The traditional approach is to use the measured battery voltage to look up a predetermined charge / discharge voltage curve to estimate the remaining battery capacity. However, the voltage curve changes as the battery ages. Generating a lookup table (e.g., an open-circuit voltage (OCV) table) for aging batteries can be very time-consuming and may not be applicable to all batteries. Therefore, there is a need for improved battery monitoring technology to improve the quality of estimated battery health (condition). Summary of the Invention

[0005] In view of this, the present invention provides a device and method for estimating the health status of a battery to solve the above-mentioned problem.

[0006] According to a first aspect of the present invention, a method for estimating battery health is disclosed, comprising:

[0007] Collect battery measurements over multiple charge and discharge cycles;

[0008] assigning a score to the measurement according to a scoring rule stored in a memory of the device; and

[0009] The battery health is calculated based on an average of the measurements, each of the measurements having an assigned score greater than a threshold.

[0010] According to a second aspect of the present invention, a device for estimating a battery health status is disclosed, comprising:

[0011] Battery;

[0012] a measurement system to collect measurements of the battery during multiple charge and discharge cycles;

[0013] a memory for storing scoring rules; and

[0014] Processing systems for:

[0015] assigning a score to the measurement value according to the scoring rule stored in the memory; and

[0016] The battery health is calculated based on the average of the measurements, each of which has an assigned score greater than a threshold.

[0017] The method for estimating battery health of the present invention includes: collecting battery measurements over multiple charge and discharge cycles; assigning scores to the measurements according to a scoring rule stored in a device memory; and calculating the battery health based on an average of the measurements, where each measurement has an assigned score greater than a threshold. In this manner, as the battery ages, the battery health meter can adjust the estimated battery health by changing how the battery measurements are collected and scored. This adjustment can be performed continuously over the life of the battery. Therefore, as more battery measurements are collected and analyzed, the estimate of battery health can be continuously improved, resulting in a more accurate estimate of battery health and information related to the battery health in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a block diagram illustrating a device operable to estimate battery health according to one embodiment.

[0019] Figure 2 is a block diagram illustrating a battery health gauge according to one embodiment.

[0020] Figure 3 An example of trigger points for collecting battery measurements is illustrated according to one embodiment.

[0021] Figure 4 An example of measurement rules for collecting battery measurements according to one embodiment is illustrated.

[0022] Figure 5 An example of a score table for scoring battery measurements is illustrated according to one embodiment.

[0023] Figure 6 is a flow chart illustrating a method for estimating battery health according to one embodiment. DETAILED DESCRIPTION

[0024] In the following detailed description of the embodiments of the present invention, reference is made to the accompanying drawings, which form a part hereof and in which are shown by way of illustration certain preferred embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice them, and it is understood that other embodiments may be utilized and that mechanical, structural, and procedural changes may be made without departing from the spirit and scope of the present invention. Therefore, the following detailed description should not be construed as limiting, and the scope of the embodiments of the present invention is defined solely by the appended claims.

[0025] It will be understood that although the terms "first," "second," "third," "primary," "secondary," etc., may be used herein to describe various elements, components, regions, layers, and / or portions, these elements, components, regions, layers, and / or portions should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer, or portion from another region, layer, or portion. Thus, a first or primary element, component, region, layer, or portion discussed below could be referred to as a second or secondary element, component, region, layer, or portion without departing from the teachings of the present inventive concept.

[0026] In addition, for ease of description, spatially relative terms such as "below," "under," "under," "above," and "over" may be used herein to describe the relationship of one element or feature to another element or feature as shown in the figures. Spatially relative terms are intended to encompass different orientations of the device in use or operation in addition to the orientations depicted in the figures. The device can be oriented in other ways (rotated 90 degrees or in other orientations), and the spatially relative descriptors used herein should likewise be interpreted accordingly. In addition, it will also be understood that when a "layer" is referred to as being "between" two layers, it can be the only layer between the two layers, or one or more intervening layers can also be present.

[0027] The terms "approximately", "roughly" and "about" generally mean within the range of ±20% of the specified value, or ±10% of the specified value, or ±5% of the specified value, or ±3% of the specified value, or ±2% of the specified value, or ±1% of the specified value, or ±0.5% of the specified value. The specified values ​​of the present invention are approximate. When not specifically described, the specified values ​​include the meanings of "approximately", "roughly" and "about". The terms used herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. As used herein, the singular terms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms used herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0028] It will be understood that when an "element" or "layer" is referred to as being "on," "connected to," "coupled to," or "adjacent to" another element or layer, it can be directly on, connected to, coupled to, or adjacent to the other element or layer, or intervening elements or layers may be present. In contrast, when an element is referred to as being "directly on," "directly connected to," "directly coupled to," or "immediately adjacent to" another element or layer, there are no intervening elements or layers present.

[0029] Note: (i) like features will be indicated by like reference numerals throughout the figures and will not necessarily be described in detail in every figure in which they appear, and (ii) a series of figures may show different aspects of a single item, each aspect being associated with various reference labels which may appear throughout the sequence or may appear only in selected figures of the sequence.

[0030] Embodiments of the present invention provide a mechanism for determining the battery health of a battery-operable device. The battery health may be indicated by a state of health (SOH) indicator displayed on a screen of the device. In one embodiment, the device includes a battery health gauge to determine or estimate the battery health (battery health) based on measurements of the battery. The device collects measurements of the battery during normal use of the battery and the device. The battery health (status) gauge assigns a score (or rating) to each measurement using a scoring algorithm. Measurements with low scores (i.e., below a predetermined threshold) may be ignored. The battery health gauge calculates the battery health (status) based on a combination of measurements (e.g., an average). The scoring algorithm may include an evaluation of a set of scoring rules.

[0031] In one embodiment, the battery health meter can update scoring rules based on measurements and / or other indications to improve accuracy. For example, based on monitoring, measuring, and analyzing battery usage, the battery health meter can identify update indications that prompt an update to the scoring algorithm, such as adding new scoring rules (or additional scoring rules) customized for the device or device usage. The update can be determined by the battery health meter based on analysis of the measurements. Alternatively, the battery health meter can upload the measurements to a remote server system, which performs the analysis and sends updates to the device.

[0032] Figure 1 A device 150 including a battery health meter 100 is shown according to one embodiment. The battery health meter 100 operates to determine the health of a battery 180 that powers the device 150. In one embodiment, the device 150 may be a battery-powered mobile device, computer, phone, watch, control panel, appliance, machine, vehicle, etc. The battery 180 provides power to electronic circuits in the device 150.

[0033] In this embodiment, device 150 includes a measurement system 120, a memory system 140, a processing system 160, and a battery 180. Measurement system 120 includes circuitry for detecting and measuring the operating state (or running state) of battery 180; for example, detecting and measuring voltage, temperature, and / or current. Memory system 140 includes one or more volatile and / or non-volatile memory devices. Processing system 160 includes one or more processors and other electronic circuits, such as programmable and / or dedicated circuits. Processing system 160 is coupled to memory system 140 to access (i.e., read and write) data stored in memory system 140. Battery 180 is a rechargeable battery that includes one or more battery cells. Examples of battery cells include, but are not limited to, lead-acid battery cells, lithium-ion battery cells, nickel-cadmium battery cells, or another type of rechargeable battery cell.

[0034] exist Figure 1In one embodiment, the battery health meter 100 is part of the processing system 160. Therefore, the battery health meter 100 is a "system-side" meter that can be implemented by programmable hardware, firmware, and / or software executed by hardware circuitry within the processing system 160. A system-side meter, such as the battery health meter 100, differs from a fuel gauge integrated circuit (IC), which integrates battery measurement, monitoring, and power management functionality into a single, special-purpose, dedicated IC. Such fuel gauge ICs are typically provided by third-party vendors, are expensive, and are difficult to update. The system-side battery health meter 100 disclosed herein provides a low-cost solution for battery health monitoring and can be easily updated based on new information collected from the battery 180 and / or other batteries of the same type. Furthermore, the method for estimating (or estimating, or measuring) battery health (or battery health gauging method) employed herein differs from the principles of prior fuel gauge ICs, including, for example, using different parameters, performing different calculations, and performing different specific processes. The algorithms, rules, and parameters used by the battery health meter 100 can be updated based on battery measurements and / or data provided by the backend server system. Thus, the battery health meter 100 adapts to the changing characteristics of the battery 180.

[0035] In one embodiment, the memory system 140 stores battery parameters 141 and measurements 142. The battery parameters 141 may include battery characteristic data; for example, the battery characteristic data may include a curve describing the open-circuit voltage (OCV) and SOC of a new battery. The curve may be stored in a data structure of a table. The battery parameters 141 may be provided by the battery manufacturer. The measurements 142 are provided by the measurement system 120. The memory system 140 also includes a scoring table 170 that stores a set of scoring rules or scoring algorithms for assigning scores to the measurements 142. The scores may be used as weights to indicate the importance of each measurement. The memory system 140 also includes a set of measurement rules 190 that specify trigger conditions for collecting (or acquiring) the measurements 142. In one embodiment, when the device 150 is manufactured, a set of predefined scoring rules is loaded into the memory system 140.

[0036] Device 150 may also include interfaces (or interfaces) such as a network interface or interface 131 and a user interface or interface 132. Among other functions, user interface 132 may display the estimated battery health (condition) to a user. Network interface 131 may also include a wireless network interface and / or a wired network interface. Network interface 131 may be used to communicate with a backend remote server system to receive software or data updates; for example, updates to score table 170 and / or measurement rules 190. In one embodiment, device 150 may upload some or all of measurements 142 to the server system via network interface 131. The server system may analyze the uploaded measurements and provide updates to device 150 to improve the battery health (condition) estimate. The server system may further analyze measurements uploaded from other devices with the same type (e.g., same model, same age, etc.) of battery to generate updates and send the updates to device 150. The updates help battery health meter 100 improve the accuracy of the battery health (condition) estimate.

[0037] Alternatively or additionally, the device 150 may analyze the measurements 142 locally. By analyzing the measurements 142, the battery health meter 100 may detect update indications; for example, when the battery 180 has completed N complete charging cycles, when the maximum available capacity (Cmax) of the battery 180 has degraded over a plurality of consecutive measurement cycles, etc. Based on the analysis, the battery health meter 100 may update the scoring table 170 to adjust the scores (or scores) assigned to different measurements. The battery health meter 100 may also update the measurement rules 190 to adjust the trigger conditions that define when battery measurements are collected (or acquired). The battery health meter 100 may also add new scoring rules (or additional scoring rules) to enhance the predefined scoring rules in the scoring table 170; enhancing the predefined scoring rules in the scoring table 170 may, for example, be by tightening the data range and its corresponding quality points. For example, if a predefined scoring rule assigns a quality point of 60 to measurements where the battery temperature varies within a range of 3-5 degrees Fahrenheit, a new rule added by the battery health meter 100 may assign a quality point of 80 (i.e., a higher quality) to measurements where the battery temperature varies within a range of 2-4 degrees Fahrenheit. Figure 5 Examples of scoring rules and corresponding quality points are provided. In one embodiment, device 150 can learn to determine the quality points of these new rules through machine learning based on past battery measurements.

[0038] Thus, as the battery 180 ages, the battery health meter 100 can adjust the estimated battery health (battery health) by changing how the battery measurements are collected and scored. Adjustments can be made continuously over the life of the battery. Thus, as more and more battery measurements are collected (or acquired) and analyzed, the estimate of the battery health can be continuously improved. The battery health can include the maximum available capacity of the battery (Cmax), the current remaining charge or capacity, the current usable time, whether the device was in airplane mode when the measurement was taken (Airplane Mode (Enabled / Disabled)), the length of operating time (the length of charge and discharge time), the length of rest time (the length of time the battery was left in rest operation at the measurement trigger point), the number of charge and / or discharge cycles the battery has completed, the battery temperature range (the change in battery temperature during the measurement), the battery capacity range, the average current range, the voltage range, the coulomb difference range, and the like.

[0039] Figure 2 is a block diagram illustrating further details of the battery health meter 100 according to one embodiment. Additional details of the measurement system 120 are also provided. The measurement system 120 includes a voltage detection circuit 210 and a temperature detection circuit 220. The signals measured by the voltage detection circuit 210 and the temperature detection circuit 220 are converted from analog to digital form by an analog-to-digital converter (ADC) 230. They are then calibrated by a calibration circuit 240 to eliminate offset or error that may be introduced by the voltage detection circuit 210, the temperature detection circuit 220, and / or the ADC 230. In one embodiment, the measurement system 120 also includes a current detection circuit 250 to measure the current flowing into (charging) or out of (discharging) the battery 180. The measured current is converted from analog to digital form by an integrating ADC 260, which integrates the measured current over a period of time. The calibration circuit 270 eliminates offset or error that may be introduced by the current detection circuit 250 and / or the integrating ADC 260. The output of calibration circuit 270 indicates the change in capacity of battery 180 over the current integration period. In one embodiment, a coulomb counting circuit can implement the functions of current detection circuit 250 and integrating ADC 260. In an alternative embodiment, the current integration function can be performed by instructions executed by processing system 160. The output of calibration circuit 240 and calibration circuit 270 is sent to battery health meter 100 for estimating battery health.

[0040] In one embodiment, the measurements made by the measurement circuit are collected at a trigger point. The trigger point is the moment when the trigger condition is met. The trigger condition can be in the measurement rule 190 ( Figure 1). A measurement value may be collected at a start trigger point and another measurement value may be collected at an end trigger point. Additional measurements may be made between the start trigger point and the end trigger point. During the time period between the start and end trigger points, the battery continues to charge / discharge. Measurements are made after the battery is at rest (i.e., not operating or running) to stabilize the voltage. Each measurement value may include multiple component measurements (i.e., each measurement value may be composed of multiple different measurement value parts); for example, a voltage measurement, a temperature measurement, and / or a current measurement. The measurement circuitry outputs the measurement value (or measurements) to the battery health meter 100 for use in estimating the battery health (condition).

[0041] The battery health meter 100 determines the initial SOC at the start (or beginning) trigger point and the final SOC at the end (or ending) trigger point. The initial SOC and the final SOC may be determined based on the battery voltage and temperature measurements and the battery parameters 141 ( Figure 1 ) to determine the battery parameters 141 ( Figure 1 ) indicates the relationship between the battery voltage and the SOC of a new battery at a given temperature. The coulomb counting result indicates the change in battery capacity from the initial SOC to the final SOC.

[0042] In one embodiment, the battery health meter 100 includes a calculation module 310 to calculate the current maximum available capacity (Cmax) of the battery 180 based on the battery capacity change and the SOC change. For example, Cmax can be calculated as the ratio of the battery capacity change to the SOC change from the start trigger point to the end trigger point. The calculation module 310 can further calculate the ratio of Cmax to the battery rated capacity to obtain the state of health (SOH). The calculation module 310 can average multiple measurements collected over multiple charge / discharge cycles to calculate the SOH. In one embodiment, the calculation module 310 can average the K measurements with the highest scores (K is a predetermined integer). In one embodiment, each measurement is given a timestamp indicating the time when the measurement was collected. The calculation module 310 can average the K highest-scoring measurements collected over the past T time units. The calculation module 310 then sends the SOH to the display 350 as an indication of the battery health (condition).

[0043] The battery health meter 100 may also include a compensation module 320 to compensate for battery aging, battery temperature, and / or battery load. In one embodiment, the compensation module 320 reads the measurements 142 from the memory system 140 and adaptively corrects the battery parameters 141. The battery parameters 141 may include zero-current voltage (ZCV), depth of discharge (DOD), internal resistance, and maximum available capacity (Cmax) at different temperatures. In one embodiment, the compensation module 320 may use the measurements 142 to calculate compensation based on an assigned fraction. The calculation module 310 calculates SOC and SOH estimates based on the output of the compensation module 320.

[0044] In terms of temperature compensation, the compensation module 320 can interpolate (or insert values) the battery parameters 141 at different temperatures to obtain the battery parameters at the measured temperature, so that the calculation module 310 can calculate the SOC and SOH more accurately.

[0045] Regarding loading compensation, the compensation module 320 may use the DOD information in conjunction with the average discharge current of the battery 180 to determine a load factor reflecting the instantaneous load of the battery 180 , thereby compensating an SOC calculation based on the loading factor.

[0046] Regarding aging compensation, the compensation module 320 calculates the difference in internal resistance of the battery 180 between the stored battery parameters 141 and the actual condition estimated from the measurements. The compensation module 320 determines an aging factor (or factors) accordingly and uses the aging factor (or factors) to adjust the battery parameters 141.

[0047] refer to Figure 1 and Figure 2The battery health meter 100 may also include a score assignment module 330 that assigns a score (or rating) to each measurement 142 using a set of scoring rules (e.g., scoring rules stored in the scoring table 170). The score assignment module 330 applies one or more scoring rules to the measurement and, for each applicable scoring rule, assigns a corresponding per-factor quality point to the measurement. The sum of all per-factor quality points is the score assigned to the measurement (i.e., all per-factor quality points are summed to obtain the score or rating for the measurement). For example, the measurement may include battery temperature data (from which the battery temperature range is calculated) and current data (from which the average current is calculated). If the measured battery temperature range is less than the battery temperature range specified in the scoring rule, the measurement may be assigned a per-factor quality point of 100 for battery temperature. If the average current is greater than the average current specified in another scoring rule, the measurement may be assigned a per-factor quality point of -50. In this example, the assigned (i.e., overall) score for the measurement is equal to the sum of 100, -50, and the per-factor quality points for the other applicable scoring rules (if any).

[0048] The battery health meter 100 may also include an update module 340 for detecting an update indication to update the scoring table 170. The update indication may indicate that the scoring table 170 may contain outdated information or may be used to upgrade the scoring table 170. The update module 340 may update the scoring rules over the life of the battery based on analysis of measurements. The update module 340 detects the update indication from battery data or measurements collected over time. Non-limiting examples of battery data or measurements may include the following: battery capacity range, battery temperature, coulomb count difference range, number of charge / discharge cycles, average current, zero current voltage (e.g., ZCV1 and ZCV2), OCV trigger time (i.e., the time at which the device 150 collects (or acquires) battery data or measurements), execution time length, suspend time length, device operating (or running) mode (e.g., airplane mode), etc. Thus, the scoring table 170 is not static but rather adapts to changes in battery characteristics as the battery ages.

[0049] In one embodiment, the update module 340 can perform an analysis on the measurements 142 to detect update indications and calculate updates to the score table 170 based on the analysis. Alternatively or additionally, the battery health meter 100 can upload the measurements 142 to a server system for the server system to perform analysis. The server system then sends updates to the score table 170 to the device 150. The upload of the measurements 142 can be performed periodically, intermittently, or on demand. In one embodiment, the server system can perform analysis based on measurements from multiple batteries of the same model and / or similar age to calculate score updates and download the score updates to the devices in which the batteries are installed. The device 150 can select updates related to its battery 180 to update its score table 170.

[0050] Figure 3 is a diagram for collecting battery measurements (e.g. Figure 1 Graph of examples of trigger points of measured values ​​142 in FIG. Figure 3 The figure shows the relationship between battery voltage (Vbat) and time. Trigger points mark the instants or time periods at which battery measurements are collected. For example, the first trigger point (TP1) is the starting trigger point (also known as the initial latch) marking the beginning of a measurement cycle, and the second trigger point (TP2) is the ending trigger point (also known as the ending latch) marking the end of a measurement cycle. In one embodiment, the measurement circuit measures the battery voltage and temperature at TP1 and TP2 and performs coulomb counting from TP1 to TP2. In one embodiment, additional measurements can be performed at other times between TP1 and TP2. In this embodiment, battery measurements can be collected or collected over time, and TP2 does not necessarily indicate the end of measurement. For example, battery measurements can be collected between TP3 and TP4, between TP5 and TP6 (not shown), and so on. In other words, in this embodiment, battery measurements can be continuously collected as long as the trigger conditions are met, thereby more accurately determining the battery health or battery charge level, and obtaining a more accurate estimate of the battery health and related information in real time.

[0051] Each trigger point is the moment a predefined trigger condition is met. For example, one trigger condition might be a fully charged battery and rested for 30 minutes (or any other set length of time). Another trigger condition might be a fully discharged battery and rested for 30 minutes (or any other set length of time). Yet another trigger condition might specify a state of charge (SOC) (e.g., SOC = 30% or 70%) and a rest time of N minutes. The rest time can be included as part of the trigger condition to allow the battery to rest after the charging or discharging process and for its voltage to stabilize. Resting refers to the state where the current flowing into or out of the battery is less than a preset threshold. For example, a state of rest can be considered when the current flowing into or out of the battery is very low. For example, a fully charged battery and resting may be when the battery is fully charged and stops discharging, with power being provided by a charger (or transformer). A fully discharged battery and resting may be when the user device (UE) is in idle or standby mode (not sending or receiving packets) and is not powered on, and the current flowing out of the battery is very low (less than a preset threshold).

[0052] Figure 4 A set of measurement rules (e.g., Figure 1 An example of measurement rules 190 in ). The measurement rules define a set of trigger conditions (trigger conditions) for collecting battery measurements, such as voltage, temperature, and current measurements. The battery health meter 100 uses measurement rules to identify trigger conditions. In one embodiment, the trigger condition indicates a given battery capacity and a given length of battery rest time. For example, the first trigger condition (TC1) can be resting for t1 minutes; and the battery is fully charged or fully discharged. The second trigger condition (TC2) can be resting for t2 minutes; and SOC = 70%. The third trigger condition (TC3) can be resting for t3 minutes; and SOC = 30%. Of course, the trigger conditions can also be other and can be freely set or changed as needed.

[0053] Figure 5 A scoring table (e.g., Figure 1170 in ). The scoring table (scoring rules) is used to assign a score to each measurement collected based on the measurement rules 190. The scoring table defines a set of scoring rules for scoring the measurements. The scoring rules specify scoring factors and corresponding individual factor quality points (e.g., P1-P9, each representing a number (score)) from which the assigned score (or assigned score, assigned score) is calculated. Each scoring factor or factor represents an operating characteristic of a battery, where the operating characteristic can be calculated from a measurement value or can also be an operating (or running) mode of the battery. Examples of scoring factors (or scoring factors) include, but are not limited to: whether the device is in airplane mode when the measurement is taken (airplane mode (enabled / disabled)), operating time (charge and discharge time), rest time (time the battery is kept in rest at the measurement trigger point), the number of charge and / or discharge cycles the battery has completed, battery temperature range (change in battery temperature during the measurement), battery capacity range (change in battery capacity during the measurement; for example, 30% to 70% (one charging cycle)), average current range for one measurement cycle, voltage range for one measurement cycle, coulomb difference range for one measurement cycle; for example, from 2300mAh to 3000mAh in one charging cycle. These predetermined factors (or factors) can be assigned corresponding quality scores (or quality points), such as P1, P2, P3, etc. When a measurement value has an assigned score (or rating) below a predetermined threshold, the battery measurement value can be ignored. For example, if the collected measurement value has a large deviation from the previously collected measurement value, such a large deviation value cannot represent the normal state of the battery. There may be many reasons for the large deviation of the measurement value. From a statistical perspective, such large deviation measurements need to be eliminated to avoid affecting the normal results. Therefore, in the present invention, only assigned scores (or ratings) greater than the predetermined threshold are selected. The battery health meter 100 can use the average of multiple measurements to estimate the battery's SOC and SOH.

[0054] Figure 6 is a flow chart illustrating a method 600 for estimating battery health according to one embodiment. For example, the method 600 may be combined with Figure 1 and Figure 2 It should be understood that these embodiments are for illustration purposes only; other devices or circuits may perform method 600.

[0055] Method 600 begins at step 610, where the device collects (or gathers) measurements of the battery during multiple charge and discharge cycles (or cycles). At step 620, the device assigns a score to the measurements (collected measurements) based on a scoring rule stored in memory. At step 630, the device calculates the battery health based on an average of the measurements, where each measurement used in the calculation has an assigned (assigned) score greater than a threshold. That is, only the assigned scores greater than the threshold are used to arrive at an average, from which the battery health is calculated. In one embodiment, the device may repeat steps 610-630 over the life of the battery.

[0056] In one embodiment, the updating of the scoring table may be performed after the battery has been used for a period of time and multiple cycles of battery measurements have been collected and analyzed. In one embodiment, the device may perform analysis on the measurements to detect an update indication. Alternatively, the device may upload the measurements to a server system that analyzes measurements from other devices and other measurements to determine updates to the scoring table. In addition to updating the scoring table, in one embodiment, the update may also include updating the measurement rules 190 ( Figure 1 ) and / or battery parameters 141( Figure 1 ) updates.

[0057] Already referenced Figure 1 and Figure 2 The exemplary embodiments describe Figure 6 However, it should be understood that Figure 6 The flowchart can be operated by Figure 1 and Figure 2 In addition to the embodiments of the present invention, embodiments of the present invention may perform operations different from those discussed with reference to the flowcharts. Figure 6 The flowcharts illustrate a particular order of operations performed by certain embodiments of the present invention, but it should be understood that such order is exemplary (e.g., alternative embodiments may perform operations in a different order, combine certain operations, overlap certain operations, etc.).

[0058] Embodiments of the present invention may be implemented as an apparatus, method, or computer program product stored in a computer-readable medium (storage medium). Thus, these embodiments may be implemented using a complete hardware combination, a complete software combination, such as software, firmware, instructions, microcode, or a hybrid of software and hardware combinations. In this disclosure, all possible combinations are referred to as "meters," "modules," or "systems."

[0059] Those skilled in the art will readily appreciate that many modifications and variations of the apparatus and method can be made while maintaining the teachings of the present invention.Accordingly, the above disclosure should be interpreted as being limited only by the metes and bounds of the appended claims.

Claims

1. A method for estimating battery health, characterized in that include: Collect battery measurements over multiple charge and discharge cycles; assigning a score to the measurement according to a scoring rule stored in a memory of the device; as well as calculating the battery health based on an average of the measurements, each of the measurements having an assigned score greater than a threshold; Also included: updating the scoring rule during the battery life based on the analysis of the measurement value; Updates to the scoring rules also include: uploading the measurements from the device to a server system to perform analysis; and An update to the scoring rule is received from the server system, wherein the update is based on an analysis of uploaded measurements of a plurality of batteries.

2. The method according to claim 1, wherein Updates to the scoring rules also include: analyzing the measured value by the device; detecting an update indication based on the analysis; and Additional scoring rules are generated based on this analysis.

3. The method according to claim 1, wherein The scoring rule specifies scoring factors and corresponding individual factor quality points from which the assigned score is calculated, and wherein each of the scoring factors is indicative of an operating characteristic of the battery.

4. The method according to claim 3, wherein Also includes: The assigned score is calculated by summing the corresponding individual factor quality points.

5. The method according to claim 1, wherein The allocated score also includes: calculating a scoring factor specified by the scoring rule measured during a charge or discharge cycle; and The measured scoring factor is compared with the scoring factor specified in the scoring rule to obtain a first single factor quality point, and the allocation score is calculated based on the first single factor quality point.

6. The method according to claim 5, wherein The scoring factors specified by the scoring rule include one or more of the following: battery temperature range, battery capacity range, average current range, voltage range, operating time length, rest time length, and the number of charge and / or discharge cycles that the battery has completed.

7. The method according to claim 1, wherein The scoring rule also specifies whether airplane mode is enabled for the device.

8. A device for estimating battery health, characterized in that include: Battery; a measurement system to collect measurements of the battery during multiple charge and discharge cycles; Memory, storing scoring rules; as well as Processing systems for: assigning a score to the measurement value according to the scoring rule stored in the memory; as well as Calculate the battery health based on the average of the measured values, each of which has an assigned score greater than a threshold; The processing system is further operative to update the scoring rules during the life of the battery based on analysis of the measurements; Updates to the scoring rules also include: uploading the measurements from the device to a server system to perform analysis; as well as An update to the scoring rule is received from the server system, wherein the update is based on an analysis of uploaded measurements of a plurality of batteries.

9. The device according to claim 8, characterized in that The scoring rule specifies scoring factors and corresponding individual factor quality points from which the assigned scores are calculated, and wherein each scoring factor is indicative of an operating characteristic of the battery.

10. The device according to claim 8, characterized in that The scoring rule specifies scoring factors including one or more of the following: battery temperature range, battery capacity range, average current range and voltage range, operating time length, rest time length, and the number of charge and / or discharge cycles that the battery has completed.

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